Wastewater is a complex mixture of organic and inorganic impurities, suspended solids, nutrients, saprotrophic and disease-causing bacteria and other microbes. When untreated wastewater is discharged into the rivers, seas, or oceans, it causes harm to human and aquatic life. Therefore, it is necessary to monitor the wastewater quality before diverting it into receiving water. The main aim of this study was the selection of an appropriate aggregation function to propose the wastewater quality index (WWQI) which is suitable for monitoring the spatial and seasonal variations of wastewater quality in the stormwater flow channel (SWF) located in Kolkata, India. Two different aggregation functions, i.e., weighted geometric mean function and weighted arithmetic mean function, were tested and analysed with primary data. Twelve wastewater quality parameters were selected. And, sampling was done seasonally for a 1-year period from December 2018 to December 2019 at eight selected locations along the SWF channel. The relative weights of each parameter were calculated based on their relative significance. Sub-index rating curves were generated to each parameter for WWQI calculations. The results revealed that weighted arithmetic mean function produced higher values of WWQI than geometric mean function. Furthermore, sensitivity analysis was carried out to evaluate the aggregation function that best suits the data of the SWF channel. The sensitivity analysis also revealed that weighted arithmetic mean function, being linear and free from ambiguity and less eclipsing, was more appropriate for measuring the WWQI for the SWF channel. Therefore, the study concluded that weighted arithmetic mean function was the most suitable aggregation function to calculate the WWQI for the SWF channel.
Keywords: Aggregation functions; Ambiguity; Arithmetic function; Eclipsing; Geometric function; Wastewater.
© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.